A novel method for the inverse QSAR/QSPR based on artificial neural networks and mixed integer linear programming with guaranteed admissibility
A novel method for the inverse QSAR/QSPR based on artificial neural networks and mixed integer linear programming with guaranteed admissibility
复制标题
基于人工神经网络和混合整数线性规划的保证可接受性的逆QSAR/QSPR新方法
DOI:
--
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Rachaya Chiewvanichakorn
中科院分区:
文献类型:
--
作者:
Masaki Waga;Eienne Andre;Atsuko ITOKAZU;Rachaya Chiewvanichakorn
影响因子:
2.2
作者:
K. Roy;A. Saha
通讯作者:
A. Saha
DOI:
10.1016/s0021-9673(00)01274-7
发表时间:
2001
期刊:
Journal of chromatography. A
影响因子:
--
作者:
M. Jalali;Mohammad Hossein Fatemi
通讯作者:
Mohammad Hossein Fatemi
影响因子:
5.6
作者:
Fujiwara, Hiroki;Wang, Jiexun;Akutsu, Tatsuya
通讯作者:
Akutsu, Tatsuya